{"id":"https://openalex.org/W7014207244","doi":null,"title":"Object-centric Mapping","display_name":"Object-centric Mapping","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W7014207244"},"language":"en","primary_location":{"id":"pmh:oai:digital.library.adelaide.edu.au:2440/132889","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/2440/132889","pdf_url":"https://digital.library.adelaide.edu.au/server/api/core/bitstreams/11f5a55a-e121-410b-834d-755aa72a4a32/content","source":{"id":"https://openalex.org/S4306401835","display_name":"Adelaide Research & Scholarship (AR&S) (University of Adelaide)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I5681781","host_organization_name":"The University of Adelaide","host_organization_lineage":["https://openalex.org/I5681781"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://digital.library.adelaide.edu.au/server/api/core/bitstreams/11f5a55a-e121-410b-834d-755aa72a4a32/content","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Li, Kejie","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li, Kejie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.975600004196167,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.975600004196167,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.012500000186264515,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.00559999980032444,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/object-pose-estimation","display_name":"object pose estimation","score":0.6119999885559082},{"id":"https://openalex.org/keywords/object-detection","display_name":"object detection","score":0.5789999961853027},{"id":"https://openalex.org/keywords/imm-filter","display_name":"IMM filter","score":0.9610000252723694},{"id":"https://openalex.org/keywords/frodo","display_name":"Frodo","score":0.7820000052452087},{"id":"https://openalex.org/keywords/outdoor-scenes","display_name":"outdoor scenes","score":0.5540000200271606},{"id":"https://openalex.org/keywords/dynamic-environments","display_name":"dynamic environments","score":0.3499999940395355}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7875000238418579},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.7293999791145325},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6852999925613403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6606000065803528},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6395999789237976},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5861999988555908},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5525000095367432},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5146999955177307},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.45260000228881836},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4318000078201294},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4189000129699707},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4097999930381775},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.4088999927043915},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4002000093460083},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.37619999051094055},{"id":"https://openalex.org/C20894473","wikidata":"https://www.wikidata.org/wiki/Q1116105","display_name":"Object model","level":3,"score":0.3743000030517578},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C181095308","wikidata":"https://www.wikidata.org/wiki/Q1541599","display_name":"Geometric primitive","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.32269999384880066},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C112604564","wikidata":"https://www.wikidata.org/wiki/Q7489226","display_name":"Shape analysis (program analysis)","level":3,"score":0.27630001306533813},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C201276399","wikidata":"https://www.wikidata.org/wiki/Q249389","display_name":"Deep-sky object","level":3,"score":0.2711000144481659},{"id":"https://openalex.org/C2776863239","wikidata":"https://www.wikidata.org/wiki/Q7936601","display_name":"Visual hull","level":3,"score":0.257999986410141},{"id":"https://openalex.org/C29123130","wikidata":"https://www.wikidata.org/wiki/Q874709","display_name":"Computational geometry","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25360000133514404},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.25220000743865967},{"id":"https://openalex.org/C146159030","wikidata":"https://www.wikidata.org/wiki/Q7625099","display_name":"Structure from motion","level":3,"score":0.25099998712539673},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.24740000069141388},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.24400000274181366},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.24240000545978546},{"id":"https://openalex.org/C14551309","wikidata":"https://www.wikidata.org/wiki/Q4636325","display_name":"3D single-object recognition","level":4,"score":0.24079999327659607},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.23970000445842743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.23819999396800995},{"id":"https://openalex.org/C2777897806","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3D modeling","level":2,"score":0.2321999967098236},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.2305999994277954}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:digital.library.adelaide.edu.au:2440/132889","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/2440/132889","pdf_url":"https://digital.library.adelaide.edu.au/server/api/core/bitstreams/11f5a55a-e121-410b-834d-755aa72a4a32/content","source":{"id":"https://openalex.org/S4306401835","display_name":"Adelaide Research & Scholarship (AR&S) (University of Adelaide)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I5681781","host_organization_name":"The University of Adelaide","host_organization_lineage":["https://openalex.org/I5681781"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Thesis"}],"best_oa_location":{"id":"pmh:oai:digital.library.adelaide.edu.au:2440/132889","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/2440/132889","pdf_url":"https://digital.library.adelaide.edu.au/server/api/core/bitstreams/11f5a55a-e121-410b-834d-755aa72a4a32/content","source":{"id":"https://openalex.org/S4306401835","display_name":"Adelaide Research & Scholarship (AR&S) (University of Adelaide)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I5681781","host_organization_name":"The University of Adelaide","host_organization_lineage":["https://openalex.org/I5681781"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Thesis"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7014207244.pdf","grobid_xml":"https://content.openalex.org/works/W7014207244.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1959608418","https://openalex.org/W2143776582","https://openalex.org/W2253156915","https://openalex.org/W2560722161","https://openalex.org/W2603429625","https://openalex.org/W2606840594","https://openalex.org/W2748348302","https://openalex.org/W2770907521","https://openalex.org/W2883993491","https://openalex.org/W2911758669","https://openalex.org/W2948913018","https://openalex.org/W2951309005","https://openalex.org/W2964121744","https://openalex.org/W3007919940","https://openalex.org/W3030163527","https://openalex.org/W3030520226","https://openalex.org/W3034259269","https://openalex.org/W3056795521","https://openalex.org/W3090308608","https://openalex.org/W3092584126","https://openalex.org/W3095753995","https://openalex.org/W3174960126","https://openalex.org/W4394671432"],"related_works":["https://openalex.org/W3035269921","https://openalex.org/W4385569643","https://openalex.org/W3092156660","https://openalex.org/W4206120224","https://openalex.org/W2970154526","https://openalex.org/W4288809167","https://openalex.org/W4403346311","https://openalex.org/W3194241004","https://openalex.org/W4313016343","https://openalex.org/W6979372663"],"abstract_inverted_index":{"This":[0,22,213],"thesis":[1],"focuses":[2],"on":[3,171,191,233,276,279,337],"building":[4],"an":[5,10,39,52,67,217,287,306,346,391],"object-centric":[6,98,266,307,409],"3D":[7,46,121,319],"map":[8,308],"given":[9],"RGB":[11,127,288],"image":[12,225,289],"sequence,":[13],"in":[14,100,109,249,298],"which":[15],"the":[16,36,55,61,81,174,245,252,357],"basic":[17],"elements":[18],"are":[19],"object":[20,114,122,144,200,229,235,247,281,293,315,353,375,378],"instances.":[21],"is":[23,70,140,344,400],"fundamentally":[24],"different":[25],"from":[26,124,310],"conventional":[27],"visual":[28],"Simultaneous":[29],"Localisation":[30],"and":[31,63,74,90,207,220,231,291,296,327,339,369,380,390,414],"Mapping":[32],"(SLAM)":[33],"that":[34,303],"describes":[35],"geometry":[37,89,206],"of":[38,57,66,118,176,180,313,351,359],"environment":[40,53],"using":[41,133,222],"geometric":[42,64],"entities,":[43],"such":[44,227],"as":[45,228,285,403],"points,":[47],"voxels":[48],"or":[49],"surfels.":[50],"Representing":[51],"at":[54,238],"level":[56],"objects":[58],"captures":[59],"both":[60,223,412],"semantic":[62],"information":[65],"environment.":[68,82],"It":[69,283,371],"more":[71,260],"natural,":[72],"compact,":[73],"closer":[75],"to":[76,96,136,142,156,185,258,273,322],"how":[77,141],"human":[78],"beings":[79],"perceive":[80],"Specifically,":[83],"we":[84,150,242,304,361],"investigate":[85],"methods":[86],"where":[87],"well-studied":[88,205],"deep":[91,110,134,165,209],"learning":[92,111,166],"can":[93],"be":[94],"combined":[95],"achieve":[97],"mapping":[99,267,410],"general":[101,338],"scenes.":[102,416],"We":[103,194,262],"first":[104,265],"build":[105],"upon":[106],"recent":[107],"advances":[108],"for":[112,377,387,394,411],"single-view":[113,199,246,280],"reconstruction,":[115],"a":[116,125,152,177,186,197,208,299,311,318,323,328,373,383,404],"task":[117],"recovering":[119],"full":[120],"shape":[123,145,211,219,236,297,384,388],"single":[126],"image.":[128],"An":[129],"open":[130],"question":[131,139],"when":[132,189],"networks":[135],"solve":[137],"this":[138,148,163,250],"generate":[143,157],"efficiently.":[146,161],"To":[147,355],"end,":[149],"propose":[151],"novel":[153],"multi-view":[154],"representation":[155],"dense":[158,329],"point":[159,325],"cloud":[160],"Although":[162,241,332,396],"pure":[164],"paradigm":[167],"shows":[168,334],"impressive":[169],"results":[170,336],"synthetic":[172],"data,":[173],"lack":[175],"large":[178],"amount":[179],"annotated":[181],"real":[182,192],"images":[183],"leads":[184],"domain":[187],"gap":[188],"inference":[190,239],"images.":[193],"then":[195],"introduce":[196,263],"new":[198,214],"reconstruction":[201,248],"method":[202],"by":[203],"combining":[204],"learned":[210,234],"prior.":[212],"approach":[215],"optimises":[216],"object\u2019s":[218],"pose":[221,379],"2D":[224,314],"cues,":[226],"silhouette,":[230],"constraints":[232],"prior":[237],"time.":[240],"only":[243],"address":[244,356],"work,":[251],"online":[253,347],"refinement":[254],"makes":[255],"it":[256,343,406],"straightforward":[257],"incorporate":[259],"observations.":[261],"our":[264,277],"system":[268,348],"\u2013":[269],"FroDO":[270,333],"(From":[271],"Detections":[272],"Objects)":[274],"based":[275],"works":[278],"reconstruction.":[282],"takes":[284],"input":[286],"sequence":[290],"infers":[292],"location,":[294],"pose,":[295],"coarse-to-fine":[300],"manner,":[301],"meaning":[302],"reconstruct":[305],"starting":[309],"set":[312],"detections,":[316],"through":[317],"bounding":[320],"box,":[321],"sparse":[324],"cloud,":[326],"mesh":[330],"progressively.":[331],"promising":[335],"cluttered":[340],"indoor":[341,413],"scenes,":[342],"neither":[345],"nor":[349],"capable":[350],"handling":[352],"motions.":[354],"limitations":[358],"FroDO,":[360],"subsequently":[362],"present":[363],"MO-LTR":[364],"(Multiple":[365],"Object":[366],"Localisation,":[367],"Tracking,":[368],"Reconstruction).":[370],"combines":[372],"monocular":[374],"detector":[376],"scale":[381],"prediction,":[382],"embedding":[385],"network":[386],"modelling,":[389],"IMM":[392],"filter":[393],"tracking.":[395],"each":[397],"component\u2019s":[398],"contribution":[399],"relatively":[401],"incremental,":[402],"system,":[405],"achieves":[407],"dynamic":[408],"outdoor":[415]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-10T00:00:00"}